Emerging Concepts Multifractal Distributions of Species and Biomass

The underlying complexity of interactions and species distributions is displayed when detailed (high-frequency) observations are made of the spatial and temporal distributions of biomass and species. There is now much evidence to show that the underlying distribution of the plankton and the MPB are fractal or multifractal. Similarly, high-frequency observations in catchments show similar multifractal and even paradoxical properties of hydrological and nutrient loads. So underlying all the generalizations discussed above lies a pattern of behavior which gives strong evidence of self-generated complexity which arises from the pandemonium of interactions between species and functional groups. Indeed, we can probably argue that the kinds of general, system level, responses described above would not occur if it were not for the underlying complexity. While making high-level statements about ecosystem behavior possible, these small-scale, multifractal properties (and the possibilities created by emergence) cause problems when we wish to make predictions at the meso-scale level of dominant species and functional groups. Because of the work that has been done across the levels of organization, coastal lagoons are very good examples of a new kind of ecology -an ecology of resilience and change, rather than an ecology and equilibrium and stasis.

One fundamental problem that these new insights reveal is that most of the data we presently use for the analysis of coastal lagoons are collected too infrequently to be useful for anything other than the analysis of broad trends. Data collected weekly or less frequently are strongly aliased and cannot reveal the true scales of pattern and process. It is just possible to analyze daily data for new insights and processes but high-frequency data - collected at scales of hours and minutes - reveal a wealth of new information. Aliased data combined with frequentist statistical techniques that 'control error' actually remove information from multifractally distributed data and raise the possibility of serious type I and II errors in ecological interpretations. Most importantly, there is information contained in the time series of multivariate data that can be collected from coastal systems. Most analyses of ecological data from ecological systems use univariate data and because of the infrequent data collection schedules - including gaps and irregular time intervals - time series analyses are not possible.

We are just beginning to find new technologies and techniques to study the high-frequency multivariate behavior of these systems using moorings and other in situ instruments. New electrode technologies make on-line access to data possible and throw up new possibilities for new kinds of observations of system state. We are beginning to realize that in addition to the 'top down' causation of climate and trophic interactions, there is also a 'bottom up' driver of complexity and the strong possibility of the emergence of high-level properties from the interactions between individuals. New forms of statistical analyses display information in time series of complex and emergent systems. This emerging understanding of complexity and emergent properties changes the ways in which we should approach EIS and risk assessments. We now know that interactions and self-generated complexity, together with hysteresis effects at the system level, can cause surprising things to happen as a result of anthropogenic change. Coastal lagoons are now classic examples of this. That means that risk assessments and EIS cannot look at impacts and changes in isolation; somehow we must develop integrated risk assessment tools that examine the interactive and synergistic effects of human impacts on coastal ecosystems. A further level of complexity is contained in the similar complex and emergent properties of the interactions between agents in the coupled environmental and socioeconomic (ESE) system in which all coastal lagoons are set. Multiple use management decisions are set in a complex web of ESE interactions across scales. Decisions made about industrial and engineering developments for financial capital reasons influence both social capital and ecological (natural capital) outcomes. Feedbacks ensure that this is also a highly nonlinear set of interactions. What we do know is that the prevalent practices of coastal management and exploitation are not resilient in the face of extreme events and that they do not degrade 'gracefully' when impacted by hurricanes and tsunamis. New management practices will be required.

See also: Mangrove Wetlands.

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